Method and system for monitoring and controlling a multi-variable process throughout a plurality of distinct phases of the process

ABSTRACT

A control of a multi-variable process throughout a plurality of successive, distinct operational phases of the process involves accumulation of sets of values of the process and quality variables (a-j) from previous multiple operations of the process through all its phases, as respective datasets of a historical record. Each dataset includes an identifier (p) of the phase to which it relates. The current values of the applicable process variables (Qa-Qh) during each phase and the phase identifier (p) are indicated on respective axes (Xp,Xa-Xh) of a multi-dimensional display in relation to an operational envelope which defines bounds (UL,LL) for the values of the individual process and quality variables (a-j) relevant to that phase and which is derived from the datasets of the historical record identified with that phase. Changes in the current process variables (Qa-Qh) result in changes of the bounds (UL,LL), and alarm is given when a current value departs from within them. Either manually or automatically correction of an alarm condition is made in accordance with calculation of required change of value of one or more manipulatable process variables (a-c).

This application is a national stage completion of PCT/GB2008/003105filed on Sep. 15, 2008 which claims priority from British ApplicationSerial No. 0717991.4 filed on Sep. 15, 2007.

FIELD OF THE INVENTION

This invention relates to multi-variable operations.

BACKGROUND OF THE INVENTION

The invention is particularly concerned with methods of operating acontrollable multi-variable process and systems for use in the operationof such a process. Methods and systems of this kind are described inGB-A-2 363 647 and GB-A-2 378 527 in which a multi-dimensional displayrepresentation of the variables is derived according to individual,parallel or other spaced coordinate axes. The variables of the processare of two kinds, namely, process variables, of which the current valuesare generally-available during process operation, and quality-variables,of which the values are generally determined later by laboratory orsimilar measurement or analysis. A boundary or envelope for prospectiveoperation of the process is defined within the system of axes inaccordance with sets of values for the process and quality variablesaccumulated as a historical record of a multiplicity of previous,satisfactory operations of the process. Each previous operation isdefined as a respective datapoint consisting of a set of values for theindividual process and quality variables applicable to that operation.

The method and system described in GB-A-2 378 527 involves thecalculation and use of an envelope termed the BOZ, representing the bestoperating zone of the process. The BOZ is calculated from a selected,limited group of the historical record of datapoints so the envelope ofthe BOZ lies wholly within the outer, boundary envelope derived from thefull historical record. The two envelopes are used for differentpurposes in the known methods and systems, the outer envelope for thepurpose of revealing the region within which operation of the processmay take place satisfactorily within the bounds of past experience. Theenvelope of the BOZ, on the other hand, establishes the ranges of theindividual process variables that are applicable to realisation of‘good’ results and provides a prediction of the ranges of thequality-variables that can be expected to be achieved.

The methods and systems as known from the above references areapplicable to the control (whether direct or indirect) of, for example,industrial manufacturing or processing operations carried out ascontinuous or single-phase processes. It is an object of the presentinvention to provide a method of operating a controllable multi-variableprocess, and a system for use in the operation of such a process, thatare of wider applicability.

SUMMARY OF THE INVENTION

According to one aspect of the present invention there is provided amethod for control of a multi-variable process throughout a plurality ofsuccessive, distinct phases of the process, wherein sets of values ofthe process and quality variables from previous multiple operations ofthe process through all the phases are accumulated as respectivedatasets of a historical record, the current values of the processvariables applicable to the current phase of the process are indicatedon respective axes of a multi-dimensional display representation ofthose variables according to individual coordinate axes, the currentvalues of the applicable process variables being indicated on theirrespective axes in relation to an operational envelope which definesbounds for the values of the individual process variables relevant tothat phase and which is derived from the datasets of the historicalrecord relevant to that phase, and wherein the process is controlledthrough each successive phase in dependence upon the bounds defined bythe operational envelope for the process variables relevant to thatphase.

According to another aspect of the present invention a system forcontrol of a multi-variable process throughout a plurality ofsuccessive, distinct phases of the process, comprises means foraccumulating sets of values of the process and quality variables fromprevious multiple operations of the process through all the phases areaccumulated as respective datasets of a historical record, means forproviding a multi-dimensional display of current values of the processvariables applicable to the current phase of the process, according toindividual coordinate axes, means indicating the current values of theapplicable process variables on their respective axes in relation to anoperational envelope which defines bounds for the values of theindividual process variables relevant to that phase and which is derivedfrom the datasets of the historical record relevant to that phase, andmeans controlling the process through each successive phase independence upon the bounds defined by the operational envelope for theprocess variables relevant to that phase.

Industrial processes often involve more than a single phase, in that rawmaterials go through a number of different operations in sequence toproduce the final product; such processes are commonly referred to asplural- or multi-phase batch processes. As a very simple example ofbatch processing used in the preparation of food, in particular friedpotatoes, the potatoes are, in a first phase, washed and scrubbed, arepart-boiled in a second phase, and are then fried in a third phase. Thevariables and their relationships in each phase of this overalloperation are different and therefore require different models. Even ifthe same equipment is used during two or more of the phases, and if thesame operations variables, such as pressure and temperature, aremeasured by the same sensors during different phases, their operationalranges may be distinctly different.

Processing-control of the various phases could be carried out asseparate operations, but it would be very time-consuming and tedious forthe user to build and subsequently to maintain, and it would not ensurethat the model objectives of each phase were necessarily consistent withthe overall objective of the plural-phase process. The present inventionenables the whole of a plural-phase industrial process to be modelled asa consistent whole. By this, sub-models of the process for the differentphases can be automatically established and run sequentially, orseparately, as required.

In setting up the method and system of the invention, the user dividesthe process into its distinct phases; the process may already by itsnature be clearly divided, or the user may make the division applyinghis/her process-engineering analysis of the process. Each phase isnumbered and this number becomes an additional variable in the overallmodel. A table is then created of all the variables (including phasenumber) that are applicable in the overall process and for what purposein each individual phase, indicating for each phase whether they areapplicable, and if so whether they can be manipulated in that phaseEnvelope selection is made by the user once for the entire process withsub-sets of envelopes for the individual phases automatically created soas to assure consistency of the objectives of each phase with theobjectives of the overall process.

BRIEF DESCRIPTION OF THE DRAWINGS

A method and system according to the present invention will now bedescribed, by way of example, with reference to the accompanyingdrawings, in which:

FIG. 1 is a schematic representation of a system according to theinvention in the context of collection and utilisation of data derivedfrom operation of a multi-variable processing plant during one of asuccession of operational phases;

FIG. 2 is illustrative of a plot in multi-dimensional space defined byparallel coordinate axes, of operation of the multi-variable processingplant of FIG. 1 during said one phase;

FIG. 3 shows in part a multiplicity of plots corresponding to that ofFIG. 2 resulting from successive operations of the multi-variableprocess in said one phase;

FIG. 4 is illustrative of the display of convex hulls in the system ofFIG. 1;

FIGS. 5 to 7 are illustrative of successive displays provided accordingto the invention in connection with operation of the method and systemof the invention; and

FIG. 8 shows an alternative form of display representation that may beused in the method and system of the invention.

DETAILED DESCRIPTION OF THE DRAWINGS

The example of method and system to be described is related to thecontrol of operation of a plural-phase multi-variable process carriedout by a basic processing-plant. Details of the plant and its purposeare not of consequence, and indeed the method and system of theinvention are related more specifically to operation of the plant as anexample of a multi-phase multi-variable process rather than to thepurpose of the process performed, being applicable in the generality toany situation involving a multi-phase multi-variable process.

In the context of initial description of the present specific example,there are fourteen variables involved in plant-operation, and of these,eleven are process or control variables to the extent that their valuesdetermine the outcome of the process. The remaining three variables arequality variables in the sense that their values define, or moreespecially are defined by, that outcome. It is to be understood,however, that not all fourteen variable are necessarily involved orrelevant in each phase of the process, and that in general the number ofprocess or control variables in particular, may vary from one phase andanother depending on the nature of the phase.

Referring to FIG. 1, the plant 1 has an input 2 and an output 3 betweenwhich there are, for example, a multiplicity of processing stages 4. Theprocessing within each stage 4 is carried out in accordance with one ormore variables that, in this example, are regulated by elevencontrollers 5. The values of these variables for each operation or ‘run’of the process are communicated to a data collection unit 6 to beaccumulated in a store 7. The term ‘run’ in this context may refer to adiscrete operation of the process during a first of several operationalphases, but it may also refer to what applies at a discrete point intime within continuous operation.

The outcome at the output 3 of each run of the process, is submitted toa unit 8 for analysis in respect of its quality as determined in thisexample according to three variables. The values of these three qualityvariables are accumulated in a store 9, so that each run of the processand its outcome is defined by an accumulated set of control values inthe store 7 and quality values in the store 9.

As the process is run again and again, a multiplicity of different setsof values is accumulated. Each set of values (‘dataset’) is made up of aplurality of sub-sets of data accumulated during the different phases ofeach run. The sub-sets for the different phases are distinguished fromone another by the ‘value’ of a phase-number variable attached to themin the respective dataset.

A selection is made from the multiplicity of datasets accumulated toprovide a historical record in the stores 7 and 9 of successive runsrepresenting satisfactory operation of the process. This record is usedin the method of the present invention as a basis for selection of thevalues of the various variables appropriate during the successive phasesof the process, to achieving a particular, successful outcome.

The values of each individual dataset held in the stores 7 and 9, arebrought together in a merge unit 10 and each scaled to the range 0 to 1.The scaled values are then processed in a unit 11 to plot them in anelectronic display unit 12. The scaled values of each dataset areplotted in multi-dimensional space using a system of parallelcoordinates as illustrated in FIG. 2, which shows by way of example, thesituation in which the fourteen control and quality values are plottedfor one of the phases of the process, but not all fourteen will be validor meaningful in all phases.

Referring to FIG. 2, the fourteen values are plotted on fourteenequally-spaced, parallel axes X01-X14 representing the fourteenvariables respectively. The first three axes, X01-X03, are used for thequality variables, and the plots are joined up to form a polygonal lineL that is representative of the single fourteen-value operating point ofthe process. The other sub-sets of process values for the same phase areeach correspondingly plotted against the same axes X01-X14 resulting ina multiplicity of polygonal lines corresponding to the line L; this isillustrated in part in FIG. 3. Each polygonal line is representative forthe respective phase of an individual operating point or run of theprocess taken from the historical record.

Referring further to FIG. 3, convex hulls H for all pairs of adjacentvariables of the parallel-axis system, are calculated in the unit 11(although convex hulls are used in the present example, other forms ofenvelope may be adopted). Between each pair of adjacent axes X01-X14there will be an upper and lower hull H defining upper and lowerlimiting boundaries between those two axes, of the operating-pointlines. The upper and lower hulls H of the successive pairs of adjacentaxes join together to define top and bottom bounds or chains TC and BCrespectively. The convex hulls applicable to all other pairings ofvariables are also calculated. The calculation is carried out for eachseparate phase, so a sub-set of envelopes is generated for each sub-setof each dataset accumulated in the stores 7 and 9.

Once the calculation of all the convex hulls for each individual phasehas been completed, the upper and lower hulls H between adjacent axes,restricted for simplicity to those parts lying within the range 0 and 1,are communicated to the unit 12 for display in respect of that phase asillustrated by FIG. 4. The upper and lower hulls H between adjacent axesare represented in the display as joining up together as top and bottomchains TC and BC respectively, which define (for example, in colour red)the upper and lower boundaries of a region within which feasibleoperation of the process can take place. Clearly, the larger the numberof historical sets of operational data used, with as wide as possiblerange of values for the individual variables, the more accurately willthis region be defined.

The system also operates to determine appropriate warning alarm levelson plant variables for each successive phase of process operation, andto display these alarm levels and the current values of thecorresponding variables to the process operator. This is achieved asillustrated in FIG. 1, using a further electronic display unit 13,however, it is possible for the functions of the units 12 and 13 to becombined into one unit. The display unit 13 is driven from an algorithmsunit 14 in accordance with data from the unit 11 and the values of theprocess variables in real time, supplied from the unit 6.

Whenever a new set of values for the process variables is received, theunit 14 determines which, if any, of the variables have values lyingoutside a region or zone defined intermediate the top and bottom chainsTC and BC of the relevant phase. The top and bottom chains TC and BC aredefined by the convex hulls applicable between the variables of adjacentaxes, but the convex hulls between all the other pairings of variablescalculated by the unit 11, overlap them so that there is in general anarrower region or zone within which successful operation can beexpected to lie. This narrower zone, nominally the ‘best operating zone’(‘BOZ’), defines in relation to each variable the range of value whichthat variable may have due to the value of each other variable.Accordingly, the unit 14 determines in dependence upon data receivedfrom the unit 11, the upper and lower limits of these ranges, andwhether the current value of any of the processing variables signalledfrom the unit 6 is outside the BOZ. If the current value of any variableis outside the BOZ, warning is given by indicating this condition in thedisplay of unit 13 or otherwise, and action is taken to determine whatchange or changes are appropriate to correct the situation.

The display unit 13 provides representation of warning alarm limits forall variables of the current phase simultaneously. These limits arealways calculated using the current values of all the other variables;no model-fitting or statistical assumptions are required, and it is tobe understood that reference to ‘current’ values does not preclude theuse of time-lagged values of some variables.

The general form of display provided by the unit 13 is illustrated ineach of FIGS. 5 to 7, and the method of operation outlined above willnow be described in relation to them during one phase of the multi-phaseoperation. The number of process variables displayed is dependent onwhich of the different phases of the process is current. Forillustrative purposes, the current phase applicable in the case of FIGS.5 to 7 is assumed to involve ten variables a-j, of which variables i andj are assumed to be quality variables and variables a-h processvariables. Of the process variables, variables a-c are assumed to bemanipulatable in the sense of being directly controllable in the currentphase.

Referring to FIG. 5, the current values Qa-Qh of the process variablesa-h derived from the unit 6 are plotted in the display of unit 13against respective axes Xa-Xh of a system of ten parallel axes Xa-Xj.The phase-number p identifying the current phase is displayed on afurther axis Xp to the left of the axis Xa. At the same time, upper andlower limits for the individual variables a-h calculated for theindividual phase by the unit 14 are plotted on their respective axesXa-Xh and joined up to provide polygonal, upper- and lower-limit linesUL and LL. The lines UL and LL delineate the applicable BOZ. Chains Tcand Bc (corresponding to chains TC and BC respectively of FIG. 4) andrepresenting bounds defined by the convex hulls between the variables ofadjacent axes are shown plotted in FIG. 5 (and also in FIGS. 6 and 7),but are optional.

The values of the quality variables i and j are assumed not to beavailable at the relevant run-time and so no values for them are plottedor shown in the display. However, upper and lower limits for each ofthem are calculated by the unit 14 from the current values of theprocess variables a-h. Although the requirement for the values of theprocess values a-h to be inside the BOZ sets ranges on the qualityvariables i and j, the ranges due to the current values of the processvariables a-h, may be narrower than those specified in selecting the BOZand hence give useful information.

As each new set of current values is received from the unit 6, thedisplay changes, and the limits on all the variables are re-calculatedand shown in the display of unit 13.

In the case illustrated in FIG. 5, the plotted values Qa-Qh are allwithin the current BOZ defined between top and bottom chains Tc and Bcrespectively, but this is not so in the circumstances of the displayillustrated in FIG. 6.

The circumstances of FIG. 6 are those in which the current values Qa-Qhhave changed resulting in consequential re-location of the lines UL andLL. The changes have, for example, located the value Qb virtually on theline LL, but it together with each of the values Qa, Qc-Qf and Qh remainwithin the newly-applicable BOZ. The value of Qg plotted on the axis Xgis, however, below the lower limit LL, and the unit 14 in response tothis signifies the existence of an alarm condition. In this respect andas at least part of the alarm condition, the unit 14 enters a caret (forexample of colour red) in the display indicating where, and in whichsense, the BOZ has been violated. More particularly, in this example, anupwardly-directed caret UC is displayed on the axis Xg where the line LLintersects that axis, to signify that the value Qg is either on or belowthe line LL. In the event that the value Qg had been on or above theline UL a similar, but downwardly-directed, carat would have beendisplayed on the intersection of the line UL with the axis Xg.

The process operator can interact with the display unit 13 to adjust oneor more of the fixed values Qa-Qc up or down their respective axesexperimentally, to see the effect this has on the limits of the othervariables. When an alarm condition exists, and several variables are onor beyond their limits, adjusting the value of even one of them may befound to move the limit lines UL and LL outwardly from one anothersufficiently to relieve the alarm condition on the others. Accordingly,using the on-line display of unit 13 in this mode, the operator can notonly monitor the current settings and results of the process, but canalso be made aware of alarm situations and receive guidance in focussedinvestigation of the remedial action necessary.

As well as identifying alarm conditions, however, the system is operablein a mode in which the unit 14 calculates a set of changes in theprocess variables that can be manipulated, in this example the variablesa-c, which will clear the alarm condition. These changes can bedisplayed immediately to the process operator so that he/she mayimplement them; they may also, or alternatively, be communicated to aprocess controller for direct, automated implementation.

FIG. 7 shows the result of automatic operation of the system tocalculate changes in the variables a-c which will be effective to clearthe alarm condition represented in FIG. 6.

Referring to FIG. 7, the calculation carried out by the unit 14 in thisexample, determines that the optimum changes required to clear the alarmcondition resulting from the current value of Qg outside the BOZ, ischange in the values of variables a and c. More particularly, thechanges required are reductions of the values of both variables a and c,and such changes are shown in the display by corresponding movements ofthe dot-representations of the values Qa and Qc to new locations on therespective axes Xa and Xc positions. The unit 14 in response to thechange of values re-calculates the upper and lower limits of eachvariable and indicates them with fresh lines UL and LL in the display ofunit 13.

The former values of the changed variables are retained as open-centredots OQa and OQc, and the former limits applicable are shown as linesOUL and OLL, for reference purposes until the changes indicated havebeen implemented. It may even be useful to show the operator informationabout earlier time-steps. For example, the lines UL and LL could befaded rather than erased each time a new set of data is received, sothat the display of the limits for one time-step would vanish over apre-selected number of time-steps. Alternatively, depending on what theprocess operator found most useful, the area enclosed by the lines ULand LL might be filled in with solid colour (for example, lime green)that would be faded at each time-step, with the intensities due to a setnumber of time-steps up to the latest, being additive so that the partof the feasible region which has been feasible throughout the largestnumber of time-steps would have the most-intense colour.

It follows from what has been described and explained above that itwould be necessary to have available within stores 7 and 9 a significantamount of historical operating data; such data is available from thedata bases normally forming part of conventionalprocess-instrumentation. Data collected over a number of differentnon-contiguous periods may be combined, and in some circumstances datagenerated by a mathematical model may be used.

Referring further to FIG. 1, the data collected comprises process dataaccumulated in store 7 and quality data accumulated in store 9. Thisdata as merged in the merge unit 10, is examined to make a selection ofall datapoints which are satisfactory in terms of the values of all thequality and process variables (a “datapoint” in this regard consists ofa set of measurements of all process and quality variables made at onetime; some variables may be time-shifted by a constant amount withrespect to others). The operator makes the selection from a large set ofhistorical operating data merged in the unit 10, that is to say, a largeset of datapoints, representative of the full range of operation of theplant, and selects those that represent good operation. Good operationis typically defined by the values of a number of quality variablesbeing within a specification, plus some other conditions such as limitson certain emissions from the plant, or on those emissions as aproportion of throughput. The selected datapoints constitute the BOZdataset and form part of the input to the algorithm unit 14 from whichthe BOZ envelope (in this example represented by a two-dimensionalconvex hull) is calculated for display by the unit 13. The BOZ datasetremains stored in memory, and the BOZ envelope calculated at eachtime-step for the current values of the process variables is displayedby the unit 13 in the manner of FIGS. 5 to 7 to indicate the limits onthe operating variables.

While the process is operating, the values of the quality variablesaccumulated in store 9 will in many cases not be available, as they areobtained from analysis of the product of the process. In this case thealgorithms unit 14 uses only the process variables whose values areavailable in real time. Conceptually, the envelope of the BOZ in themulti-dimensional space defined by all the variables is projected intothe multi-dimensional subspace defined by the process variables, and theprocess is required to remain within this projected envelope. Thisprojected envelope is the envelope of the values of the processvariables for all historical datapoints for which the values of theprocess variables and the values of the quality variables weresatisfactory.

The algorithms unit 14 in the present context operates according to acontrol algorithm as well the alarm algorithm referred to above. Asuitable algorithm for this purpose is described in GB-A-2 378 527. Thisuses a planar convex hull, but it would also be possible to derive acontrol algorithm from the constraints obtained by fitting anyconvenient closed hyper-geometric figure to the BOZ.

In the event that one or more alarms are identified from the alarmalgorithm at a time-step, the control algorithm is operative todetermine first whether any variables are outside their absolute limits.Absolute limits on variables apply regardless of the values of any othervariables; absolute limits are shown by upper and lower horizontal lines‘1’ and ‘0’ respectively of FIGS. 5 to 7 using separate envelopes foreach phase. There are more restrictive absolute limits than thoseindicated by the horizontal lines, namely the maximum and minimum valuesin the BOZ dataset for the current BOZ. If any manipulated variables(a-c in the example of FIGS. 5 to 7) are outside their absolute limits,they will have to be moved within those limits as part of the alarmrectification, but if any non-manipulated variables are outside theirabsolute limits, the alarm cannot be fully rectified.

The present invention enables the process to meet “targets” on processvariables; a “target” on a variable specifies that the value of thatvariable should not be below some greater-than-or-equal-to (GE) targetvalue, and/or should not be above some less-than-or-equal-to (LE) targetvalue. Targets, which are different from the BOZ, may not always besatisfied even during good operation, and they may be imposed onnon-manipulated as well as manipulated variables. Control of the processconsists of changes to the values of the manipulated variables only.These must be such as to cause the values of the non-manipulatedvariables to move into their targets in a time that depends on theprocess dynamics of the system.

Operation of the system in the above respect begins with selection of asubset of the datapoints in the BOZ dataset that have the current phasenumber and satisfy all the required targets. The selection is madeautomatically to form a target dataset, and the envelope of the targetdataset is constructed within the unit 14 for display by the unit 13 asan inner envelope within the BOZ.

An example of an inner envelope as displayed by the unit 13 isillustrated in FIG. 5, the envelope in this case having upper and lowerlimits represented by the polygonal lines UI and LI respectively, withinthe limits UL and LL of the BOZ envelope. The values of all the processvariables in this specific example lie within the inner envelope, but ingeneral some will lie outside it and action will be required towardsbringing them all within it.

The principle used is that if all the manipulated variables are movedinside the inner envelope the non-manipulated variables will follow.Accordingly, the system calculates the changes in the values of themanipulated variables required to bring them all inside the innerenvelope, and displays these changes to the process operator via thedisplay unit 13. The operator may implement these changes manually orthey may be fed online to be implemented automatically, so that processoperation is improved according to the user's target criteria. Theimprovement does not appear immediately but after a time which dependson the process dynamics and the control system.

An inner envelope may also be used to advantage where a non-manipulatedvariable is in alarm, and no moves of manipulated variables can be foundthat will move its limits out to include its current value. In thesecircumstances, the inner envelope is used to find moves of manipulatedvariables that will cause the value of the non-manipulated variable tomove inside its violated limit. As the limit cannot be changed by movingmanipulated variables, it is treated for this purpose as though fixed,and a working target is set on the non-manipulated variable that is inalarm. If its upper limit is violated, an LE target value equal to thevalue of the upper limit minus a suitable quantity, is set, whereas ifthe lower limit is violated, the setting is of a GE target value equalto the value of the limit plus the same quantity. The moves of themanipulated variables that will cause the value of the alarmednon-manipulated variable to move to the working target are thencalculated using an inner envelope in the same way as moves to bring amanipulated variable to a specific target are found as described above.As before, the changes required to bring about these moves are displayedto the operator, and may be implemented by him/her manually orautomatically. In either case the result is that the values of thenon-manipulated variables that are in alarm change in due course toclear the alarms.

The method and system of the invention also provides for optimisation ofthe process and quality variables during each phase. This is ofadvantage in those circumstances where the process is required to runwith the value of a process variable as high as possible or as low aspossible, or where the value of a process variable is required to be ashigh as possible provided it does not exceed some LE target value, or aslow as possible provided it does not fall below some GE target value. Ifthere are non-manipulated process variables to be maximised orminimised, then a dynamic inner envelope is used. For eachnon-manipulated variable to be maximised a top limit is either thecurrent upper limit on that variable due to the BOZ and the values ofthe other process variables, or the LE target value of that variable ifit exists. The bottom limit for that variable in the inner envelopestarts at its current value. Similarly, for any non-manipulated variableto be minimised the top limit is its current value and its bottom limitis either its current lower BOZ limit or its GE target value if any.

The subset of datapoints selected for calculation of the inner envelopein this case are the datapoints of the BOZ dataset for the currentphase, which are within the limits on the non-manipulated variables thatare to be maximised or minimised. The inner envelope calculated fromthese datapoints is then shrunk by raising the bottom limits on thenon-manipulated variables to be maximised and lowering the top limits onthe non-manipulated variables to be minimised, until the envelope cannotbe shrunk any further. This latter condition is reached when furthershrinking would lead either to there being too few datapoints of theoriginal selection remaining from which to construct the inner envelope,or to one of the manipulated variables being kept outside the shrunkinner envelope by its current BOZ limits. The fully-shrunk innerenvelope is displayed to the process operator via the unit 13 togetherwith the changes in the values of the manipulated variables required tobring them into the envelope. The required changes may be implementedmanually by the operator or they may be fed online to be implementedautomatically, with the result that after a time which depends on theprocess dynamics and the control system, the values of the variables tobe maximised increase and those of the variables to be minimiseddecrease.

If a manipulated variable is to be maximised or minimised, the innerenvelope provides limits on how far it can be moved without an adverseeffect on the non-manipulated variables to be optimised.

A further feature of the invention lies in automatic ‘tightening’ of theBOZ envelope. If process operation consistently outperforms the originalBOZ criteria then a subset of the BOZ dataset is selected to define aninner envelope that is to act effectively as a new BOZ, and amaximum-acceptable alarm rate is specified. The new BOZ is selected suchthat, had it been in use for the last n sets of process-variable values,where n is an integer appropriate to the process, the number of thosesets of process-variable values for which there were alarms would nothave exceeded the specified maximum. The effect of this is that so longas the process is kept within the limits due to the new BOZ, processoperation is improved compared with remaining within the wider, old BOZ.This facility provides for continuous improvement as the process and itsoperator learn to stay within each successively tighter BOZ.

The display of BOZ envelopes, inner envelopes, alarms and recommendedprocess movement as described above may also, or as an alternative, bedisplayed on a circular plot (sometimes known as a ‘radar plot’ or‘spider diagram’) rather than in the linear forms illustrated in FIGS. 5to 7. In this case the axes are arranged as the spokes of a wheel withequal angles between them, as illustrated in FIG. 8 for a circular plotof twelve variables Xa-Xl. An indication of the current phase number isprovided also, either as a general indication or on a thirteenth axis(not shown). All calculations are performed using the parallelcoordinate system, it being the display alone that is transformed tocircular form.

Referring to FIG. 8, polygonal lines UL and LL (for example in green,represented here in dashed line) show the current upper and lower limitsrespectively on the variables. In this case the lines UL connecting theupper limits form a closed figure, as do the lines LL connecting thelower limits. Dots Qa-Ql (for example in blue) representing the currentvalues of the process variables are joined by a solid (blue) line toassist the operator to recognise the ‘shape’ of the current operatingpoint. Where a variable is outside its limits a caret (for example inred) appears at the violated limit, a caret UC (as illustrated for axesXe and Xi) where the upper limit UL is violated and a caret LC (asillustrated for axes Xa and Xd) where the lower limit LL is violated.The operation of the system to calculate and indicate the correctionsrequired to rectify the alarm condition indicated by the display of FIG.8, and to utilise inner envelopes, is unchanged with this form ofdisplay.

The method and system of the present invention have been described indetail more especially in respect of operation during one of a pluralityof phases. The same general operation is applicable during the otherphases of the overall process, but the linking together of thesedifferent-phase operations to run as an integrated whole has significantadvantages. Those advantages are achieved simply by including the phasenumber in the data of each datapoint. This allows the separation of theaccumulated data according to relevant phase to be readily carried outand transition from one phase to the next to proceed automatically.

In the method and system described above where a separate set oftwo-variable convex hulls is calculated for each phase, the displayprovided at any one time by the display unit 13 represents the situationapplicable to the one, current phase. As an alternative, one set oftwo-variable convex-hull envelopes may be calculated covering all (orpossibly, a selection of) the phases of the process operation, and inthese circumstances the phase numbers are used to select the parts ofthe envelopes relevant to the current phase.

1. A method for control of a multi-variable process throughout aplurality of successive, distinct phases of the process, comprising: (a)the step of accumulating sets of values of process and quality variablesfrom previous multiple operations of the process through all theplurality of phases, the sets of values being accumulated as respectivedatasets of a historical record, each dataset comprising a plurality ofsub-sets of data individually identified respectively with the pluralityof phases of the process; (b) determining which of the plurality ofphases is a current phase of the process; (c) deriving an operationalenvelope in respect of the current phase, the operational envelope beingderived from sub-sets of data which are individually identified in thedatasets of the historical record with the current phase; (d) indicatingon respective axes of a multi-dimensional display representation currentvalues of the process variables within the current phase of the process,the current values of the process variables within the current phasebeing indicated on their respective axes of the multi-dimensionaldisplay representation; (e) indicating the operational envelope againstthe respective axes of the multi-dimensional display representation todefine bounds for values of the process variables within the currentphase; and (f) controlling the process successively through individualphases of the plurality of phases in dependence upon the bounds definedby the operational envelope for values of the process variables withinthe current phase.
 2. The method according to claim 1, wherein eachdataset accumulated in the historical record includes an identifier ofthe phase to which the dataset relates.
 3. The method according to claim2, wherein the operational envelope for each individual phase is derivedfrom the datasets of the historical record that include the identifierof that respective phase.
 4. The method according to claim 2, whereinthe operational envelope for each individual phase is a respective partof an envelope derived from the datasets of the historical recordapplicable to one of all the phases and a selection of the phases of theprocess.
 5. The method according to claim 1, wherein an indication ofwhich phase of the process is current is indicated on a respective axisof the multi-dimensional display representation.
 6. The method accordingto claim 1, wherein the operational envelope is a convex hull.
 7. Themethod according to claim 1, wherein the bounds define as betweenprocess variables of adjacent ones of the axes, upper and lower limitsfor the values of those respective process variables.
 8. The methodaccording to claim 1, wherein the axes of the multi-dimensional displayrepresentation are parallel to one another.
 9. The method according toclaim 1, wherein the axes of the multi-dimensional displayrepresentation are spaced from one another angularly.
 10. The methodaccording to claim 1, wherein the operational envelope which definesbounds for the values of the process variables within the current phasealso defines bounds for quality variables within the current phase. 11.A system for control of a multi-variable process throughout a pluralityof successive, distinct phases of the process, comprising: (a) means foraccumulating sets of values of the process and quality variables fromprevious multiple operations of the process through all the plurality ofphases, the sets of values accumulated being respective datasets of ahistorical record each dataset comprising plurality of sub-sets of dataindividually identified respectively with the plurality of phases of theprocess; (b) means for determining which of the plurality of phases is acurrent phase of the process; (c) means for deriving an operationalenvelope in respect of the current phase, the operational envelope beingderived from sub-sets of data which are individually identified in thedatasets of the historical record with the current phase; (d) means forindicating on respective axes of a multi-dimensional displayrepresentation current values of the process variables within thecurrent phase of the process, the current values of the processvariables within the current phase being indicated on their respectiveaxes of the multi-dimensional display representation; (e) means forindicating the operational envelope against the respective axes of themulti-dimensional display representation to define bounds of the currentfor values of the process variables within the current phase; and (f)means for controlling the process successively through individual phasesof the plurality of phases in dependence upon the bounds defined by theoperational envelope for values of the process variables within thecurrent phase.
 12. The system according to claim 11, wherein eachdataset accumulated in the historical record includes an identifier ofthe phase to which the dataset relates.
 13. The system according toclaim 12 wherein the operational envelope for each individual phase isderived from the datasets of the historical record that include theidentifier of that individual phase.
 14. The system according to claim12, wherein the operational envelope for each individual phase is arespective part of an envelope derived from the datasets of thehistorical record applicable to one of all the phases and a selectionof, the phases of the process.
 15. The system according to claim 11,wherein an indication of which phase of the process is current isindicated on a respective axis of the multi-dimensional displayrepresentation.
 16. The system according to claim 11, wherein theoperational envelope is a convex hull.
 17. The system according to claim11, wherein the bounds define as between process variables of adjacentones of the axes, upper and lower limits for the values of thoserespective process variables.
 18. The system according to claim 11,wherein the axes of the multi-dimensional display representation areparallel to one another.
 19. The system according to claim 11, whereinthe axes of the multi-dimensional display representation are spaced fromone another angularly.
 20. The system according to claim 11, wherein theoperational envelope which defines bounds for the values of the processvariables within the current phase also defines bounds for qualityvariables within the current phase.